Wandering around

Let's write a simple Python application that changes its background image everytime you click on it. Here is a short code that helps you do that: import os, sys import Tkinter import Image, ImageTk def key(event): print "pressed", repr(event.char) event.widget.quit() root = Tkinter.Tk() root.bind_all(' ', key) root.geometry('+%d+%d' % (100,100)) dirlist = os.listdir('.') old_label_image = None for f in dirlist: try: image1 = Image.open(f) root.geometry('%dx%d' % (image1.size[0],image1.size[1])) tkpi = ImageTk.PhotoImage(image1) label_image = Tkinter.Label(root, image=tkpi) label_image.place(x=0,y=0,width=image1.size[0],height=image1.size[1]) root.title(f) if old_label_image is not None: old_label_image.destroy() old_label_image = label_image root.mainloop() # wait until user clicks the window except Exception, e: # Skip a...

If you want to break out of a loop in Python, just use "break". How about when you need to bread out of more than 2 loops in Python? Here is a hint: Using Raise and Exception. try:    ...    if (condition) : #You want to break your loop here       raise GetOutOfLoop except GetOutOfLoop:    pass

A salesman goes to meet 100 customers. Based on his experience, the expectation of selling goods for a customer is 40%. Find the probability that a customer will buy in 45% - 50%.

Given an object recognition system, I obtain the confident values of whether or not an object appears in an image. I want to find out whether or not an action is likely to happen given such objects' appearance probability. I can model such a system using conditional probability, e.g., the probability of action A given the appearance of object O1, and without the appearance of object O2, etc. Could Topic models or any LDA-style model help in this case?

We randomly distribute n points on the circumference of a circle. What is the probability that they will all fall in a common semi-circle? (read from here )

A random variable is a mapping from a sample space to real numbers $\Omega \rightarrow \mathrm{R}$ At a certain point in most probability courses, we don't see the sample space, but it's always there, lurking in the background. For example: Let $\Omega = \{(x,y); x^2 + y^2 \leq 1\}$ be the unit disc. Consider drawing a point "at random" from $\Omega$. Outcome: $\omega = (x,y)$. Examples of random variables: $X(\omega) = x$, $X(\omega) = y$, $Z(\omega) = x + y$

I divide my email into three categories: A1 = spam. A2 = low priority, A3 = high priority. I find that: P(A1) = .7 P(A2) = .2 P(A3) = .1 Let B be the event that an email contains the word "free". P(B|A1) = .9 P(B|A2) = .01 P(B|A3) = .01 I receive an email with the word "free". What is the probability that it is spam?